- Email: [email protected]
‘Looking beyond the male–female dichotomy’ – Sibling composition and child immunization in India, 1992–2006
Social Science & Medicine 107 (2014) 145e153
Contents lists available at ScienceDirect
Social Science & Medicine journal homepage: www.elsevier.com/locate/socscimed
‘Looking beyond the maleefemale dichotomy’ e Sibling composition and child immunization in India, 1992e2006 Prashant Kumar Singh a, b, *, Sulabha Parasuraman b a Population, Health & Nutrition Research Programme (PHN-RP), Institute for Human Development, NIDM Building, IIPA Campus, IP Estate, Mahatama Gandhi Marg, New Delhi 110 002, India b International Institute for Population Sciences Govandi Station Road, Deonar, Mumbai 400 088, India
a r t i c l e i n f o
a b s t r a c t
Article history: Received 29 July 2013 Received in revised form 5 February 2014 Accepted 7 February 2014 Available online 14 February 2014
This study examines trends in gender differentials in child immunization beyond the conventional male efemale dichotomy, by considering older surviving sibling composition between 1992 and 2006 in India. The present study adopts the World Health Organization (WHO) guidelines for appraising full immunization among children utilising three rounds of the National Family Health Survey. Twelve combinations of sex composition of surviving older siblings were constructed. Bivariate differentials and pooled multilevel logistic regression analysis were conducted to assess the trends and patterns of child immunization with respect to various categories of older surviving sibling composition. Although child immunization increased between 1992 and 2006, majority of all eligible children did not receive the recommended immunization. Further, full immunization significantly varies by twelve categories of siblings composition during 1992e2006. The probability of full immunization among male children who did not have any older surviving sibling was 60% in 2005e06, while it was just 26% among female children who had 1þ older surviving sister and brother. This study emphasizes the need to integrate sibling issues in child immunization as a prioritized component in the ongoing Universal Immunization Programme, which could be an effective step towards ensuring full immunization coverage among Indian children. Ó 2014 Elsevier Ltd. All rights reserved.
Keywords: Child immunization Gender Sibling composition India
1. Introduction The effectiveness of child immunization towards disease prevention, disability and death has been proven (Global Alliance for Vaccines and Immunization, 2012) and established as a costeffective intervention worldwide (Mulholland et al., 2012). In India, full immunization coverage has increased substantially at the national and sub-national levels over the last few years (Singh, 2013) from 35% in 1992 to 54% in 2008 (International Institute for Population Sciences, 2010). However, there is considerable divergence in administering the recommended immunization among socioeconomic groups, though immunization services are available at no cost in public health facilities (Singh, 2013; Madhavi, 2005). To illustrate, a national level survey shows that about two in five children belonged to illiterate mother received full immunization, * Corresponding author. Population, Health & Nutrition Research Programme (PHN-RP), Institute for Human Development, NIDM Building, IIPA Campus, IP Estate, Mahatama Gandhi Marg, New Delhi 110 002, India. E-mail addresses: [email protected] (P.K. Singh), sulabhap@rediffmail. com (S. Parasuraman). http://dx.doi.org/10.1016/j.socscimed.2014.02.017 0277-9536/Ó 2014 Elsevier Ltd. All rights reserved.
whereas the proportion was 75% among those children belonged to mother who had completed 10 and above years of schooling (International Institute for Population Sciences, 2010). Further, about three in five children in urban areas received immunization compared to two in five in rural areas. There is considerable regional disparity in child immunization e while some states from the southern region have coverage of over 70%, it is less than 40% among few central Indian states (International Institute for Population Sciences, 2010). Studies in low-and-middle income countries like India have documented the importance of mothers, households and community level factors associated with child immunization (Sheikh et al., 2011; Banerjee et al., 2010; Uddin et al., 2010). Additionally, factors such as accessibility to healthcare facility (Cockcroft et al., 2009), healthcare expenditure (Lauridsen and Pradhan, 2011), and infrastructure (Ghei et al., 2010) also affect levels of child immunization. In public health literature, gender differences in the provision of child immunization in the South Asia have been widely discussed (Singh, 2013; Chan and Yeoh, 2002; Arnold, 2001; Timaeus et al., 1998; Hill and Upchurch, 1995; Nag, 1991). Socioeconomic
146
P.K. Singh, S. Parasuraman / Social Science & Medicine 107 (2014) 145e153
difference in child immunization is common for majority of lowand-middle income countries (Hill and Upchurch, 1995; Edejer et al., 2005) however, gender gap is especially apparent in South Asia (Holmes, 2006; Das Gupta et al., 2003; Arnold, 2001). For instance, a recent review conducted by the WHO highlighted that gender differences in immunization coverage, favouring the male still exists in many South and South-East Asian countries (Hilber et al., 2010). There is evidence of lower full immunization coverage among female children than male children in India (Singh, 2013). A recent review based on over sixty studies conducted in different parts of India documented that childhood immunization coverage performance was better among male than among female children (Mathew, 2012). A survey carried out in Surat, India to calculate the incidence of measles among children under five years observed higher immunization coverage among male than to female children (Desai et al., 2002). Similarly, a study undertaken in Assam, India observed higher full immunization rate among male (65%) compared to female children (59%) based on the examination of vaccination cards and maternal recall (Phukan et al., 2009). An econometric analysis of vaccination data obtained from a sample of over 4333 rural children showed that 55% of the male children were fully vaccinated compared to 50% among female children (Borooah, 2004). Efforts to identify the underlying factors associated with malefemale difference in immunization highlighted that the persistence of gender discrimination resulted from the perceived greater economic, social, and religious utility of sons over daughters (Bhat and Zavier, 2003; Das Gupta et al., 2003). The cultural reasons for discrimination against daughters in the Indian context include the long history of the systematically marginalized status of women in terms of lower autonomy, restrictions on movement within the community and illiteracy, thus making daughters less socially valuable to parents than sons (Ghosh, 2012; Chamarbagwala, 2011; Das Gupta et al., 2003; Muhuri and Preston, 1991). In 1987, the ground breaking study done by Das Gupta in the state of Punjab, India emphasized that discriminatory practices against female children were not generalized, but highly selective. The study observed that such practices were highly concentrated among families with several girls (Das Gupta, 1987). The importance of death clustering, survival status of previous child, number of siblings and sex composition of older siblings on child healthcare including immunization has been documented in low-and-middle income countries including India (Arulampalam and Bhalotra, 2006; Das Gupta, 1990), Ghana (Garg and Morduch, 1998), and Bangladesh (Zenger, 1993). For instance, a study conducted in Matlab, Bangladesh found that girls with one or more older sisters were five times more at risk of dying than girls without older sisters. Similarly, for males, the mortality risk was higher for those with two or more older brothers, but the difference in mortality risk between the two was small. The authors also found that female children with two or more older brothers and male children with one or more older sister had very low levels of mortality (Muhuri and Preston, 1991). The review of available literature however, shows limited evidence of gender difference in full immunization by older sibling composition in the Indian context. Most of the studies were conducted during the early 1990s, period typically characterized as high fertility, low socioeconomic status, low status of women, poor healthcare knowledge and with limited policy initiatives. During the last one and half decades, India experienced considerable socioeconomic development along with major health policy initiatives including the Reproductive and Child Health Programme e 1997, National Population Policy e 2000, National Health Policy e 2002 etc. In all the policy initiatives, child immunization has been a
top priority (Madhavi, 2005). Since 1990s, the coverage of full immunization has increased both at national and across different socioeconomic groups (International Institute for Population Sciences and ORC Macro, 2007); the key question is whether full immunization is accessible to every child, irrespective of the sex composition? One could expect that the sibling difference has to be the lowest for healthcare that is freely available, like immunization. This study attempts to assess the progression of immunization for children aged 12e36 months over time with emphasis on gender difference by older surviving sibling composition. This study hypothesized that the gender difference in full immunization had declined over time among children with the same sex surviving sibling/s composition (female with older surviving sisters, and male with older surviving brothers), as compared to children with opposite sex surviving sibling/s composition (female with older surviving brothers, and male with older surviving sisters). Further, we also expected a declining gender gap in full immunization over time between male and female children with mixed older surviving siblings (one or more elder surviving brothers and sisters). 2. Data and methods 2.1. Data and sampling technique The present study uses data from three rounds of the National Family Health Survey (NFHS), similar to the Demographic and Health Survey (DHS) conducted during 1992e93, 1998e99 and 2005e06 (International Institute for Population Sciences and ORC Macro, 1995, 2000, 2007). All three rounds of the survey are nationally representative. The NFHS-1 covered a sample of 89,777 ever-married women aged 13e49, NFHS-2 covered 90,303 evermarried women aged 15e49, and NFHS-3 covered 124,385 women aged 15e49. A similar sampling scheme was adopted in all the three rounds of NFHS. The survey adopted a two-stage sample design in rural areas and a three-stage sample design in urban areas. In rural areas, the villages were selected at the first stage by using the Probability Proportional to Size (PPS) sampling scheme. The required number of households was selected at the second stage using systematic sampling. In urban areas, blocks were selected at the first stage, census enumeration blocks (CEB) containing approximately 150e200 households were selected at the second stage, and the required number of households were selected at the third stage using systematic sampling technique. The details of the sampling weights as well as the extensive information on survey design, data collection, and management procedures are described in the NFHS reports of the respective rounds (International Institute for Population Sciences and ORC Macro, 1995, 2000, 2007). 2.2. Defining outcome variable and sample size The outcome variable of the study is full immunization among children in the age group 12e36 months. According to the guidelines developed by the WHO, children are considered fully immunized when they receive a vaccination against tuberculosis (BCG); three doses of diphtheria, whooping cough (pertussis), and tetanus (DPT) vaccines; three doses of poliomyelitis (polio) vaccine and one dose of the measles vaccine by the age of twelve months. BCG should be given at birth or at first clinical contact, DPT and polio require three vaccinations at approximately 4, 8, and 12 weeks of age, and the measles vaccine should be given at age 12 months or soon after reaching 9 months of age. The present analysis is restricted to the last live birth (single and multiple) to women to make the estimates comparable and robust, as the information on child immunization in NFHS-1 (three live births in last four years)
P.K. Singh, S. Parasuraman / Social Science & Medicine 107 (2014) 145e153
NFHS-2 (two live births in last three years), and NFHS-3 (five live births in last five years) was not collected uniformly for all children under five years of age. The analytical sample size of the present study is restricted to 18,429, 15,795 and 15,993 children aged 12e 36 months respectively in NFHS-1, NFHS-2, and NFHS-3. The missing cases were negligible and therefore, excluded from the analysis. Information on child immunization was collected from the immunization cards shown by household members during the survey or in the absence of the immunization card, information was gathered from the mother of the respective child. In NFHS-1, about 61% mothers shown child immunization cards, and it increased to 69% in NFHS-2 and 76% in NFHS-3. The upper age limit was chosen as 36 months to maximize the use of available data. Further, the advantage of considering the immunization status of the last child is to minimize recall errors. Previous studies have shown that the precision with which mothers recall child healthcare including immunization deteriorates following the last birth (Luman et al., 2009). Besides, considering the last birth could reduce the mother’s level of unobserved heterogeneity (Arulampalam and Bhalotra, 2006). The present study takes into consideration the gender pattern of older surviving siblings with reference to the last birth. 2.3. Defining older surviving sibling composition and other predictor variables All the three rounds of NFHS asked every eligible woman in the age group 15e49 years, her complete birth history including the sex, order of birth and survival status. Using this information, several categories were created to represent the composition of older siblings based on the number and sex of older siblings’, while also taking into account the sex of the last born child. The index of the sex-sibling composition is classified into twelve categories e six older surviving sibling categories for each male and female child.
147
The six sibling categories are: ‘none’ (no older surviving brother and no older surviving sister); ‘one surviving older brother and no surviving older sister’; ‘one surviving older sister and no surviving older brother’; ‘two or more surviving older brothers and no older sister’; ‘two or more surviving older sisters and no older brother’; and a ‘mixed’ (1þ older surviving brothers and 1þ sisters) category of surviving older brothers and sisters. To examine the net effect of older surviving sibling composition on immunization during 1992e 2006, selected socioeconomic and demographic predictors have been included in the analysis. These indicators are based on their theoretical and observed importance applied in literature and availability of information in all three rounds of survey for better comparability. A detailed description of selected variables is provided in Table 1. 2.4. Analytical approach First, bivariate analyses were carried out to understand the proportion of the difference in full immunization by twelve categories of older surviving sibling composition and other background variables. To test the significance of association in full immunization by selected background characteristics, Chi-squared tests were performed. As the sampling design of the NFHS offers an opportunity to make all the three rounds of data comparable (Mishra et al., 2004), earlier studies have pooled the different rounds of DHS/NFHS datasets to observe changes over time (Singh, 2013). In order to examine the trend of full immunization coverage over time, the study fit a pooled multilevel logistic regression model while adjusting for important socioeconomic, demographic and contextual variables. The interaction results between time and sibling compositions are presented as a set of predicted probabilities with 95% confidence intervals (CI) of being fully immunized for better representation. The Wald test was used to test the significance of the interaction between sibling composition and survey
Table 1 Description of exposure variables used in modelling full immunization among children aged 12e36 months in India, NFHS 1992e2006. Background variables Individual level variables Older surviving sibling composition Current age of the child Status of the last child Preceding birth interval Mother’s childcare burden Mother’s age at last birth Mother’s education Mother’s occupation Mother’s mass media exposure Household level variables Religion Social groups Household size Household wealth quintile Contextual level variables Type of residence Region of residence
Description Constructed for the most recent surviving child between 12 and 36 months, based on mother’s complete birth history, that takes into account the sex of the most recent child, the sex composition as well as number of the surviving siblings and birth order. Based on mother’s reporting of year of birth of the last child, grouped as follows: 12e23, and >23 months Based on the mother’s reporting of the last children as wanted then, wanted later, wanted no more. The status of the child is then categorized as: wanted (wanted then) and unwanted (wanted later þ wanted no more) Indicates mother’s preceding birth interval with reference to the last child, grouped as: 24 months and >24 months Indicates women’s total number of births in the 3-year period preceding the birth of the index child: No burden and At least one burden Based on women’s reporting of year of birth of the last child and current age of women and grouped as follows: <20, 20e29, and >29 Defined using years of schooling and they were grouped as: Illiterate, 1e4 years, 5e7 years, 8e9 years, 10 and above years Identification of women’s occupation based on self-reporting and grouped as follows: not working, agricultural/domestic/ labour, and others Assessed by considering how often women read the newspaper, listen to the radio and watch television or cinema categories as: no exposure and any exposure Based on women’s self reporting religious groups as: Hindu, Muslim, and Others Identification of the social group was based on the women’s self-reporting as: Others, Scheduled Tribes, and Scheduled Castes Based on number of members in the household grouped as: up to 5, 6e9 and >9 Index based on household amenities, assets and durables derived by factor analysis used for the computation of the wealth index. Households were categorized into quintiles as follows: Richest, Richer, Middle, Poorer, and Poorest Children’s current place of residence: Urban, and Rural NFHS demarcations of regions based on geographical locations and cultural settings categorized as: North (Delhi, Haryana, Himachal Pradesh, Jammu and Kashmir, Punjab, Rajasthan and Uttarakhand); Central (Chhattisgarh, Madhya Pradesh and Uttar Pradesh); East (Bihar, Jharkhand, Orissa and West Bengal); West (Goa, Gujarat and Maharashtra); South (Andhra Pradesh, Karnataka, Kerala and Tamil Nadu); Northeast (Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim and Tripura)
148
P.K. Singh, S. Parasuraman / Social Science & Medicine 107 (2014) 145e153
year. Owing to the binary nature of the dependent variable (full immunization: yes ¼ 1, otherwise ¼ 0), the multilevel model with logit link function can be described as follows:
"
pips ln 1 pips
# ¼ a þ xips b þ wps g þ zs h þ ups þ vs
where ln(pips/(1 pips)) is the logit in which pips is the probability of children ‘i’ in Primary Sampling Unit (PSU) ‘p’ in state ‘s’ receiving full immunization; xips, wps, and zs are vectors of individual/household level, PSU level, and state level characteristics; a is a constant, while b, g, and h are vectors of estimated parameter coefficients; and ups and vs are unexplained residual terms at the PSU and state level, respectively. The study used penalized quasi-likelihood (PQL) approximate estimation procedure, which has been found to be the least biased (Rasbash et al., 2009) in the case of binary response. Since the study considered a range of covariates in the models, we examined for multicollinearity with variance inflation factors, all of which were much lower than 2.5, suggesting that the possibility of high multicollinearity was ostensible. The analysis has been performed using Stata version 10 (Statacorp, 2007). 3. Results 3.1. Description of the study population Table 2 shows the percentage of last born children in each descriptive category in last three years preceding the survey. During 1992e2006, percentage of male children was higher as compared with female counterparts. Results show higher percentage of children belonged to either male or female with 1þ older surviving brother and sister or to those who did not have any older surviving siblings. Nearly three in five children belonged to the age group 12e23 months. The unwanted status of last child increased from 20% in 1992e93 to 28% in 2005e06. The mother’s childcare burden marginally declined from 55% in 1992e93 to 53% in 2005e06. Majority of the mothers were illiterate and unemployed in all three rounds of surveys. Exposure to any type of mass media improved from 46% in 1992e93 to 69% in 2005e06. The sample distribution during 1992e2006 indicates that majority of the children were Hindus and from the ‘others’ social group. The distribution indicated more children in poor households than in higher socioeconomic households.
whose mother was exposed to any means of mass media received higher full immunization. During 1992e2006, the gap in immunization between the rich and the poor was almost three-fold. Rural children and those residing in central regions received lower full immunization during 1992e2006, whereas children belonged to urban areas and from the south region utilized higher rates of full immunization. 3.3. Sibling composition and full immunization during 1992e2006: a pooled multilevel analysis A multilevel regression model has been applied after pooling three rounds of survey to examine the net effect of sibling composition on full immunization (Appendix 1). The results suggest that factors such as sibling composition, age of the child, mother’s childcare burden, mother’s age, education, mass media exposure, religion, household size, wealth quintile, and region of residence significantly associated with the full immunization. As the prime aim of this study is to examine the trend in full immunization for the last born child and differentials according to child’s gender and older surviving sibling composition, adjusted predicted probabilities has been estimated from the pooled multilevel model (Table 4). The two-way interaction between the twelve categories of sibling composition and three categories of survey period were statistically significant after adjusting for other background variables in the model. The result clearly suggests that full immunization across the twelve categories of sibling compositions have changed significantly over time. In order to present the results more comprehensively, the difference between male compositions with a similar category of female compositions has been demonstrated. To illustrate, we have compared the similar sibling composition category between male and female children to understand the differences in full immunization. The findings confirm that with one exception (males who had only one older surviving brother e females who had only one older surviving brother), gender difference in full immunization was apparent across all sibling compositions during 1992e2006. Moreover, the results show a growing gender difference in full immunization coverage in a few categories of sibling composition during 1992e2006. For instance, the gap in full immunization between male and female who had 2þ older surviving sisters were 8% in 1992e93, that increased to about 14% in 2005e06. Similarly, those male and female who had one older surviving sisters, the gap in full immunization had increased from 2% in 1992e93 to 5% in 2005e06.
3.2. Differentials in full immunization coverage during 1992e2006 4. Discussion Differentials in full immunization by selected individuals, households and contextual level characteristics during 1992e2006 are presented in Table 3. The trend suggests that full immunization coverage at the national level increased from 36% in 1992e93 to 45% during 2005e06. Considerable difference in full immunization was evident by older sibling composition. For instance, in all three rounds of survey the lowest full immunization was observed among female children with 1þ older surviving brother and 1þ sister. However, male children who did not have any older surviving sibling received highest percentage of full immunization. The full immunization was lower among those children who had at least one older surviving sibling below the age of five years. Children born to women aged above 30 years received the lowest percentage of full immunization during 1992e2006. Differences in full immunization coverage by mother’s education were large. For example, in 2005e06, about 72% of children born to mothers who had completed ten or more years of schooling received full immunization, whereas the corresponding figure was less than 28% among children born to illiterate mothers. Children
The overall trend suggests a significant difference in full immunization among last born children according to the number and gender of older sibling compositions during 1992e2006. The analysis confirms that immunization coverage for female children worsened with the number of surviving older sisters, similarly immunization coverage for male children declined with the increase in number of older surviving brothers. On the other hand, during 1992e2006, a higher coverage of full immunization was observed among those male and female children who either did not have any older surviving sibling or had one older opposite sex sibling. Previous studies also found that both female and male children born after multiple same-sex siblings had lower immunization, whereas male children with multiple older sisters had the highest rate of immunization (Pande, 2003). Literature suggests that despite the presence of strong son preference in countries like India, parents may selectively favour a certain sex-birth-order to attain their desired sex composition (Pande, 2003). Indeed, in India the percentage of ever married
P.K. Singh, S. Parasuraman / Social Science & Medicine 107 (2014) 145e153
149
Table 2 Percentage distribution of children aged 12e36 months according to selected background characteristics, India, NFHS 1992e2006. Background variables
1992e93 %
1998e99 n
%
2005e06 n
%
n
Sex of the child Male Female
51.2 48.8
9591 8910
52.5 47.5
8424 7371
54.4 45.6
8619 7374
Older surviving sibling composition Male with no older survival sibling Female with no older survival sibling Male with only 1 brother and no sister Male with only 1 sister and no brother Female with only 1 brother and no sister Female with only 1 sister and no brother Male with 2þ brothers and no sister Male with 2þ sisters and no brother Male with 1þ brothers and 1þ sisters Female with 2þ brothers and no sister Female with 2þ sisters and no brother Female with 1þ brothers and 1þ sister
12.9 12.4 6.2 6.2 6.3 5.8 3.6 4.2 18.1 3.5 3.6 17.2
2418 2311 1195 1155 1204 1060 650 775 3326 632 664 3039
13.9 12.6 7.2 7.0 7.0 5.8 2.9 4.5 17.0 3.3 3.2 15.5
2232 1991 1165 1132 1063 905 465 718 2712 484 511 2417
14.9 12.7 7.4 8.2 7.1 5.9 3.0 4.6 16.2 2.5 3.6 13.6
2506 2240 1240 1362 1180 1017 442 738 2331 404 531 2002
Child current age 12e23 months >23 months
60.3 39.7
10,972 7457
57.4 42.6
8988 6807
56.5 43.5
8978 7015
Status of the last child Wanted Unwanted
80.5 19.5
14,799 3618
76.8 23.2
12,087 3704
72.0 28.0
11,992 3996
Preceding birth interval 24 months >24 months
26.2 73.8
3643 10,035
26.4 73.6
3093 8461
28.7 71.3
3255 7958
Mother’s childcare burden No surviving children At least one
45.4 54.6
8354 10,075
45.5 54.5
7236 8559
47.2 52.8
7925 8068
Mother’s age at last birth <20 20e29 >29
21.3 61.4 17.2
3515 11,683 3231
21.6 64.5 13.9
2985 10,304 2506
18.5 66.4 15.2
2474 10,753 2766
Mother’s education Illiterate 1e4 years 5e7 years 8e9 years 10 and above years
63.8 6.6 11.6 7.0 11.0
10,757 1287 2332 1536 2517
53.3 8.5 14.0 9.2 15.1
7896 1347 2207 1653 2692
48.3 6.6 14.9 12.5 17.7
6181 1140 2393 2382 3897
Mother’s occupation Not working Agricultural/domestic/labour Others
70.7 19.1 10.2
12,857 3571 2001
65.7 27.6 6.6
10,575 4059 1161
63.0 32.7 4.3
10,365 4544 1084
Mother’s mass media exposure No exposure Any exposure
54.1 45.9
9083 9346
45.7 54.3
6620 9175
31.2 68.8
3735 12,258
Religion Hindu Muslim Others
81.4 10.6 8.0
14,051 2419 1956
79.3 15.2 5.5
11,718 2249 1808
78.1 17.2 4.6
11,071 2655 2250
Social groups Others Scheduled Castes Scheduled Tribes
83.9 9.9 6.2
13,875 2233 2318
70.1 20.1 9.6
10,526 2883 2289
69.8 20.2 9.4
10,114 2744 2495
Household size Up to 5 members 6e9 >9 members
31.5 44.5 24.2
6121 8111 4197
35.4 43.4 21.2
5681 6924 3190
40.5 43.1 16.4
7018 6642 2333
Household wealth quintile Poorest Poorer Middle Richer Richest
23.9 23.7 20.2 16.1 16.1
4194 4031 3834 3461 2909
26.6 25.3 19.5 15.1 13.6
4297 4111 3417 2360 1610
24.8 22.0 19.2 17.9 16.0
2722 2851 3220 3545 3655
(continued on next page)
150
P.K. Singh, S. Parasuraman / Social Science & Medicine 107 (2014) 145e153
Table 2 (continued ) Background variables
1992e93
1998e99
2005e06
%
n
%
n
%
Place of residence Urban Rural
23.1 76.9
5095 13,334
23.0 77.0
4275 11,520
26.6 73.4
6272 9721
Region of residence North Central East Northeast West South Total
11.7 29.1 22.5 4.3 13.1 19.3 100
4124 4278 3070 2039 1982 2936 18,429
13.0 24.4 24.3 3.7 13.8 20.8 100
3741 2909 2950 2206 1670 2319 15,795
11.8 29.3 25.5 3.9 13.1 16.4 100
2447 3791 2532 3032 1855 2336 15,993
women in the age group 15e49, who want at least one daughter is almost as equal as (81%) the percentage who want at least one son (International Institute for Population Sciences and ORC Macro, 2007). This suggests that in societies with a strong gender bias, the preferred sex composition often includes a daughter and the possibility of bias in immunization for a male with two or more elder brothers could be higher than a male who did not have any siblings or had all opposite sex siblings. Evidence suggests greater sibling rivalry in resource distribution including parental time allocation to children’s healthcare when the number of sons is more in the family than daughters (Garg and Morduch, 1998). In this case, quite often, the younger son has to bear the adverse consequences in terms of lower education, cognitive skills and healthcare, since the household resource allocation has already been shifted to the elder brother. For example, if the rate of return on investment in healthcare is greater for the elder male than for the younger, the elder brother will receive more of such investments (Behrman et al., 1982). The present study shows an increasing gender gap in immunization by cross-sibling comparison. For instance, over time, there has been a two-fold increase in the difference in full immunization between male and female children with a mixed older surviving sibling composition (1þ older surviving brother and 1þ sister). This continuous gender difference in immunization could be linked with India’s well documented history of son preference (Das Gupta et al., 2003; Dyson and Moore, 1983). For instance, according to the third round of NFHS, over one in four married women in the age group 15e49, expressed their desire for more sons than daughters, whereas the percentage who wanted more daughters than sons was less than three percent (International Institute for Population Sciences and ORC Macro, 2007). The increasing gender difference in full immunization supports the evidence that the existence of rigid patrilineal kinship systems, whereby only sons are allowed to inherit family assets and wealth, appear to be primarily responsible for continuing gender difference, even in the face of economic development and the rising status of women (Das Gupta et al., 2003; Das Gupta and Shuzhuo, 1999; Dyson and Moore, 1983). The preference of sons over daughters is the product of prolonged societal, cultural and religious practices that promotes son(s) as a symbol of power and prestige in the community (Kishor, 1993; Pande, 2003; Choi and Lee, 2006). In these circumstances, the overall allocation of available community and household level resources could be significantly shifted towards the preferred sex.
4.1. Potential limitations This study has a few limitations. Child immunization data have been collected from two sources: vaccination cards and mothers’ reporting. Using data from both mothers’ reports and
n
immunization cards is more inclusive than data from cards alone. Previous studies have evaluated the quality of information from mothers’ reports. Some of them have underscored the high validity of mother’s recall, while other studies point to significant recall errors resulting in either overestimation or underestimation (Luman et al., 2009). In spite of potential sources of errors, the DHS (or NFHS) is considered one of the best sources of population-based information on health and healthcare service utilization in low-and middle-income countries (Murray et al., 2003). Thus, this study considers immunization coverage based on the NFHS data to be of adequate quality and validity against which other measurements of the same variables can be compared. There are other potential factors such as distance, quality of immunization services, behaviour and attitude of health personnel that could determine the full immunization coverage and act separately for male and female children, which have not been included in this study due to data constraints. This study cannot examine the causality as the study design and available data have certain restrictions.
4.2. Conclusion and policy implications According to recent estimates, about 22.6 million children were not fully vaccinated and remained at risk for diphtheria, tetanus, and pertussis and other vaccine-preventable causes of morbidity and mortality worldwide, and about 30% (6.8 million) lived in India alone (Centre for Disease Control and Prevention, 2013). The findings of the present study have potential implications for India’s health policy that has been insufficient in dealing with the sibling difference in immunization over time. It is necessary to recognize at the policy level that besides financial costs, other factors could also restrict immunization coverage. As evidences suggests that balanced gender composition of offspring may be important to parents in India, where female born after multiple same sex sibling face lower priority in healthcare (Chamarbagwala, 2011). More indepth researches are needed to examine the underlying factors that affect immunization coverage among children by sex compositions. In addition, it is important to raise awareness about the importance of child vaccination, and the role of local health workers is vital in reaching households with higher order births, and especially children with two or more elder same sex siblings. Adequate attention has not been extended to assess the full immunization coverage considering sibling compositions; rather gender (male-female) difference per se has only been considered. Thus, there is need to adopt inclusive approach to enhance the coverage of full immunization irrespective of sibling compositions. For instance, providing financial incentives could be an effective strategy to minimize full immunization differences by sibling compositions. Further, this study emphasizes the need to integrate sibling issues in child immunization as a prioritized component in
P.K. Singh, S. Parasuraman / Social Science & Medicine 107 (2014) 145e153
151
Table 3 Percentage of children of ages 12e36 months who received full immunization by selected background characteristicsa, India, NFHS 1992e2006. Background characteristic
1991e92
1998e99
2005e06
Pooled 1992e2006
Sex of the child Male Female
[p < 0.001] 37.1 34.9
[p < 0.001] 43.1 39.5
[p < 0.001] 46.0 43.1
[p < 0.001] 42.0 38.9
Older surviving sibling composition Male with no older survival sibling Female with no older survival sibling Male with only 1 brother and no sister Male with only 1 sister and no brother Female with only 1 brother and no sister Female with only 1 sister and no brother Male with 2þ brothers and no sister Male with 2þ sisters and no brother Male with 1þ brothers and 1þ sisters Female with 2þ brothers and no sister Female with 2þ sisters and no brother Female with 1þ brothers and 1þ sister
[p < 0.001] 45.6 44.4 42.2 44.7 41.3 40.7 30.3 38.2 27.9 31.4 34.6 24.7
[p < 0.001] 53.2 49.3 48.5 51.1 49.1 46.9 30.5 49.7 29.4 33.0 35.7 26.4
[p < 0.001] 56.7 54.7 50.7 54.1 51.1 53.1 40.3 49.1 29.9 35.3 36.7 27.0
[p < 0.001] 51.9 49.4 47.2 50.3 47.2 46.8 33.5 45.5 29.0 32.9 35.7 25.9
Child current age 12e23 months >23 months
[p < 0.001] 35.0 37.7
[p ¼ 0.042] 40.8 42.2
[p < 0.001] 43.5 46.2
[p < 0.001] 39.5 42.0
Status of the last child Wanted Unwanted
[p ¼ 0.031] 36.4 34.7
[p < 0.001] 42.8 36.7
[p < 0.001] 48.4 34.9
[p < 0.001] 42.1 35.4
Preceding birth interval 24 months >24 months
[p < 0.001] 35.8 32.0
[p ¼ 0.008] 39.6 37.0
[p ¼ 0.118] 40.9 38.9
[p ¼ 0.002] 38.0 36.4
Mother’s childcare burden No surviving children At least one
[p < 0.001] 40.0 32.8
[p < 0.001] 46.0 37.5
[p < 0.001] 51.4 38.6
[p < 0.001] 45.7 36.1
Mother’s age at last birth <20 20e29 >29
[p < 0.001] 35.2 38.8 27.3
[p < 0.001] 37.3 45.0 30.7
[p < 0.001] 43.1 47.0 36.4
[p < 0.001] 38.2 43.5 31.2
Mother’s education Illiterate 1e4 years 5e7 years 8e9 years 10 and above years
[p < 0.001] 24.0 44.4 49.6 62.3 70.3
[p < 0.001] 26.4 46.7 53.9 59.0 68.6
[p < 0.001] 27.5 47.8 52.5 60.8 72.0
[p < 0.001] 25.7 46.3 52.0 60.7 70.5
Mother’s occupation Not working Agricultural/domestic/labour Others
[p < 0.001] 36.6 33.0 37.8
[p < 0.001] 42.4 36.6 50.7
[p < 0.001] 48.6 35.4 56.8
[p < 0.001] 42.1 35.2 45.2
Mother’s mass media exposure No exposure Any exposure
[p < 0.001] 23.4 51.0
[p < 0.001] 25.3 54.8
[p < 0.001] 26.7 52.8
[p < 0.001] 24.8 52.8
Religion Hindu Muslim Others
[p < 0.001] 36.7 25.6 56.4
[p < 0.001] 41.7 31.5 65.9
[p < 0.001] 45.6 37.2 63.1
[p < 0.001] 41.5 31.2 62.4
Social groups Others Scheduled Castes Scheduled Tribes
[p < 0.001] 38.8 28.1 24.1
[p < 0.001] 44.1 39.5 25.6
[p < 0.001] 49.3 41.1 33.5
[p < 0.001] 44.6 36.1 27.9
Household size Up to 5 members 6e9 >9 members
[p < 0.001] 40.2 33.8 34.8
[p < 0.001] 47.7 38.1 37.4
[p < 0.001] 49.6 40.3 43.7
[p < 0.001] 46.0 37.3 38.0
Household wealth quintile Poorest Poorer Middle Richer Richest
[p ¼ 0.020] 17.3 22.2 35.5 49.4 65.0
[p ¼ 0.010] 21.1 29.7 42.8 53.5 63.8
[p < 0.001] 24.6 34.7 48.7 56.6 71.0
[p < 0.001] 21.0 28.9 42.3 53.2 66.6
Place of residence Urban
[p < 0.001] 52.2
[p < 0.001] 57.6
[p < 0.001] 58.5
[p < 0.001] 56.1 (continued on next page)
152
P.K. Singh, S. Parasuraman / Social Science & Medicine 107 (2014) 145e153
Table 3 (continued ) Background characteristic
1991e92
1998e99
2005e06
Pooled 1992e2006
Rural
31.2
36.5
39.6
35.6
Region of residence North Central East Northeast West South Total
[p < 0.001] 42.5 23.0 21.6 20.7 60.8 55.3 36.1
[p < 0.001] 41.6 21.8 27.8 22.8 65.7 67.0 41.4
[p < 0.001] 45.8 31.0 45.9 35.7 54.8 60.3 44.6
[p < 0.001] 43.3 25.5 32.1 26.2 60.3 60.7 40.5
a
Figures in parentheses are the p < value obtained from c2 test applied for each variable.
Table 4 Predicted probabilitya,b (95% Confidence Interval) obtained from the pooled multilevel regression analysis of child immunization (aged 12e36 months) for interaction between older surviving sibling compositions and survey period, India, NFHS 1992e2006. Interaction effect between older surviving sibling composition and time
Male Male Male Male Male Male Male
compositions with no older survival sibling with only 1 brother and no sister with only 1 sister and no brother with 2þ brothers and no sister with 2þ sisters and no brother with 1þ brothers and 1þ sisters
Female compositions Female with no older survival sibling Female with only 1 brother and no sister Female with only 1 sister and no brother Female with 2þ brothers and no sister Female with 2þ sisters and no brother Female with 1þ brothers and 1þ sister Differencesc Male with no older survival sibling e Female with no older survival sibling Male with only 1 brother and no sister e Female with only 1 brother and no sister Male with only 1 sister and no brother e Female with only 1 sister and no brother Male with 2þ brothers and no sister e Female with 2þ brothers and no sister Male with 2þ sisters and no brother e Female with 2þ sisters and no brother Male with 1þ brothers and 1þ sisters e Female with 1þ brothers and 1þ sister
1992e93 Predicted probability
1998e99 95% CI
Predicted probability
2005e06 95% CI
Predicted probability
95% CI
0.47 0.42 0.45 0.30 0.41 0.26
[0.46e0.49] [0.40e0.45] [0.42e0.47] [0.27e0.33] [0.39e0.44] [0.24e0.27]
0.53 0.48 0.51 0.34 0.46 0.27
[0.51e0.55] [0.45e0.50] [0.49e0.54] [0.30e0.37] [0.43e0.50] [0.26e0.30]
0.61 0.54 0.58 0.37 0.50 0.30
[0.59e0.63] [0.51e0.56] [0.55e0.60] [0.34e0.41] [0.47e0.53] [0.29e0.32]
0.44 0.43
[0.42e0.46] [0.40e0.45]
0.50 0.47
[0.48e0.52] [0.45e0.50]
0.57 0.54
[0.56e0.59] [0.51e0.56]
0.43
[0.40e0.45]
0.45
[0.43e0.48]
0.53
[0.50e0.56]
0.30 0.34 0.23
[0.27e0.33] [0.31e0.37] [0.22e0.24]
0.31 0.33 0.24
[0.28e0.35] [0.30e0.36] [0.23e0.26]
0.36 0.36 0.26
[0.33e0.40] [0.33e0.40] [0.25e0.28]
3.23
2.59
3.20
0.28
0.42
0.34
2.11
5.77
4.57
0.48
2.11
1.26
7.65
12.99
13.73
2.77
3.31
4.20
All the predicted probabilities were significantly different at p < 0.001 (c2 ¼ 243.45) in Wald test. Predicted probability adjusted for child age, mother’s childcare burden, preceding birth interval, wanted status of child, mother’s age at last birth, mother’s education, mother’s occupation, mother’s mass media exposure, religion, social groups, household size, household wealth index, place of residence, and region of residence. c Difference calculated as: male compositions female compositions*100. a
b
the ongoing Universal Immunization Programme, which could be an effective step towards ensuring full immunization coverage among all Indian children. The study recommends further research to examine why there has been little progress in reducing the differentials in child immunization by sibling composition. In future, research is required at regional, sub-regional and across different socioeconomic strata to explore further dynamics related to sibling difference in immunization. Future research should also examine the cultural and economic perspectives on sibling differences by explicitly investigating parental attitudes toward social norms.
Acknowledgement The authors are grateful to the editor and four anonymous reviewers for their insightful feedbacks on the earlier draft of the manuscript. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.socscimed.2014.02.017.
P.K. Singh, S. Parasuraman / Social Science & Medicine 107 (2014) 145e153
References Arnold, F., 2001. Son preference in South Asia. In: Sathar, Z.A., Phillips, J.F. (Eds.), Fertility Transition in South Asia. Oxford University Press, Oxford, pp. 278e297. Arulampalam, W., Bhalotra, S., 2006. Sibling death clustering in India: state dependence versus unobserved heterogeneity. Journal of Applied Statistics 169, 829e848. Banerjee, A.V., Duflo, E., Glennerster, R., Kothari, D., 2010. Improving immunisation coverage in rural India: clustered randomised controlled evaluation of immunisation campaigns with and without incentives. BMJ 340, c2220. Behrman, J., Pollak, R., Taubman, P., 1982. Parental preferences and provision for progeny. Journal of Political Economy 90, 52e73. Bhat, P.N.M., Zavier, A.J.F., 2003. Fertility decline and gender bias in Northern India. Demography 40, 637e657. Borooah, V.K., 2004. Gender bias among children in India in their diet and immunisation against disease. Social Science & Medicine 58, 1719e1731. Centre for Disease Control and Prevention, 2013. Global routine vaccination coverage, 2012. Morbidity and Mortality Weekly Report 62, 858e861. Chamarbagwala, R., 2011. Sibling composition and selective gender-based survival bias. Journal of Population Economics 24, 935e955. Chan, A., Yeoh, B., 2002. Gender, family and fertility in Asia: an introduction. AsiaPacific Population Journal 17, 5e10. Choi, J.Y., Lee, S.H., 2006. Does prenatal care increase access to child immunization? Gender bias among children in India. Social Science & Medicine 63, 107e117. Cockcroft, A., Andersson, N., Omer, K., Ansari, N.M., Khan, A., Chaudhry, U.U., Ansari, U., 2009. One size does not fit all: local determinants of measles vaccination in four districts of Pakistan. BMC International Health and Human Rights 9 (Suppl. 1), S4. Das Gupta, M., 1987. Selective discrimination against female children in rural Punjab, India. Population and Development Review 13, 77e100. Das Gupta, M., 1990. Death clustering, mothers’ education and the determinants of child mortality in rural Punjab, India. Population Studies 44, 489e505. Das Gupta, M., Shuzhuo, L., 1999. Gender Bias in China, the Republic of Korea, and India 1920-90. World Bank Policy Research Working Paper no. 2140. Available at: http://elibrary.worldbank.org/content/workingpaper/10.1596/1813-94502140 (accessed 01.10.13.). Das Gupta, M., Zhenghua, J., Bohua, L., Zhenming, X., Chung, W., Hwa-Ok, B., 2003. Why is son preference so persistent in East and South Asia? A cross-country study of China, India and the Republic of Korea. Journal of Development Studies 40, 153e187. Desai, V.K., Kapadia, S.J., Kumar, P., Nirupam, S., 2002. Study of measles incidence and vaccination coverage in slums of Surat city. Indian Journal of Pediatrics 69, 1037e1040. Dyson, T., Moore, M., 1983. On kinship structure, female autonomy, and demographic behavior in India. Population and Development Review 9, 35e60. Edejer, T.T., Aikins, M., Black, R., Wolfson, L., Hutubessy, R., Evans, D.B., 2005. Cost effectiveness analysis of strategies for child health in developing countries. BMJ 331, 1177. Garg, A., Morduch, J., 1998. Sibling rivalry and the gender gap: evidence from child health outcomes in Ghana. Journal of Population Economics 11, 471e493. Ghei, K., Agarwal, S., Subramanyam, M.A., Subramanian, S.V., 2010. Association between child immunization and availability of health infrastructure in slums in India. Archives of Pediatrics & Adolescent Medicine 164, 243e249. Ghosh, R., 2012. Child mortality in India: a complex situation. World Journal of Paediatrics 8, 11e18. Global Alliance for Vaccines and Immunization, 2012. Global Immunization News. Available at: http://www.who.int/immunization/GIN_June_2012.pdf (accessed 12.06.12.). Hilber, A.M., Bosch-Capblanch, X., Schindler, C., Beck, L., Sécula, F., McKenzie, O., Gari, S., Stuckli, C., Merten, S., 2010. Gender and Immunization: Summary
153
Report for SAGE, 2010. Partner WHO e Initiative for Vaccine Research. World Health Organization, Geneva: Switzerland. Hill, K., Upchurch, D.M., 1995. Gender differences in child health: evidence from the demographic and health surveys. Population and Development Review 21, 127e151. Holmes, J., 2006. Do community factors have a differential impact on the health outcomes of boys and girls? Evidence from rural Pakistan. Health Policy and Planning 21, 231e241. International Institute for Population Sciences, ORC Macro, 2000. National Family Health Survey (NFHS e 2), 1998e99: India. IIPS, Mumbai. International Institute for Population Sciences, ORC Macro, 2007. National Family Health Survey (NFHS e 3), 2005e06: India, vol. I. IIPS, Mumbai. International Institute for Population Sciences, ORC Macro, 1995. National Family Health Survey (NFHS e 1), 1992e93: India. IIPS, Mumbai. International Institute for Population Sciences, 2010. District Level Household and Facility Survey (DLHS-3), 2007e08. IIPS, Mumbai. Kishor, S., 1993. May god give sons to all: gender and child mortality in India. American Sociological Review 58, 247e265. Lauridsen, J., Pradhan, J., 2011. Socio-economic inequality of immunization coverage in India. Health Economics Review 1, 11. Luman, E.T., Ryman, T.K., Sablan, M., 2009. Estimating vaccination coverage: validity of household-retained vaccination cards and parental recall. Vaccine 27, 2534e 2539. Madhavi, Y., 2005. Vaccine policy in India. PLoS Medicine 2, e127. Mathew, J.L., 2012. Inequity in childhood immunization in India: a systematic review. Indian Pediatrics 49, 203e223. Mishra, V., Roy, T., Retherford, R.D., 2004. Sex differentials in childhood feeding, health care, and nutritional status in India. Population and Development Review 30, 269e295. Muhuri, P.K., Preston, S.H., 1991. Effects of family composition on mortality differentials by sex among children in Matlab, Bangladesh. Population and Development Review 17, 415e434. Mulholland, E.K., Griffiths, U.K., Biellik, R., 2012. Measles in the 21st century. New England Journal of Medicine 366, 1755e1757. Murray, C.J., Shengelia, B., Gupta, N., Moussavi, S., Tandon, A., Thieren, M., 2003. Validity of reported vaccination coverage in 45 countries. The Lancet 362, 1022e1027. Nag, M., 1991. Sex preference in Bangladesh, India and Pakistan, and its effect on fertility. Demography India 20, 163e185. Pande, R., 2003. Selective gender differences in childhood nutrition and immunization in rural India: the Role of Siblings. Demography 40, 395e418. Phukan, R.K., Barman, M.P., Mahanta, J., 2009. Factors associated with immunization coverage of children in Assam, India: over the first year of life. Journal of Tropical Pediatrics 55, 249e252. Rasbash, J., Charlton, C., Browne, W.J., Healy, M., Cameron, B., 2009. MLwiN Version 2.1. Centre for Multilevel Modelling. University of Bristol, Bristol. Sheikh, S., Ali, A., Zaidi, A.K., Agha, A., Khowaja, A., Allana, S., Qureshi, S., Azam, I., 2011. Measles susceptibility in children in Karachi, Pakistan. Vaccine 29, 3419e 3423. Singh, P.K., 2013. Trends in child immunization across geographical regions in India: focus on urban-rural and gender differentials. PLoS ONE 8, e73102. Statacorp, 2007. Stata Statistical Software: Release 10. Statacorp LP, College Station, Texas: USA. Timaeus, I., Harris, K., Fairbairn, F., 1998. Can Use of Health Care Explain Sex Differentials in Child Mortality in the Developing World. Too Young to Die: Genes or Gender. Population Division, United Nations, New York. Uddin, M.J., Koehlmoos, T.P., Saha, N.C., Khan, I.A., Shamsuzzaman, 2010. Child immunization coverage in rural hard-to-reach areas of Bangladesh. Vaccine 28, 1221e1225. Zenger, E., 1993. Sibling neonatal mortality risks and birth spacing in Bangladesh. Demography 30, 477e488.
Contents lists available at ScienceDirect
Social Science & Medicine journal homepage: www.elsevier.com/locate/socscimed
‘Looking beyond the maleefemale dichotomy’ e Sibling composition and child immunization in India, 1992e2006 Prashant Kumar Singh a, b, *, Sulabha Parasuraman b a Population, Health & Nutrition Research Programme (PHN-RP), Institute for Human Development, NIDM Building, IIPA Campus, IP Estate, Mahatama Gandhi Marg, New Delhi 110 002, India b International Institute for Population Sciences Govandi Station Road, Deonar, Mumbai 400 088, India
a r t i c l e i n f o
a b s t r a c t
Article history: Received 29 July 2013 Received in revised form 5 February 2014 Accepted 7 February 2014 Available online 14 February 2014
This study examines trends in gender differentials in child immunization beyond the conventional male efemale dichotomy, by considering older surviving sibling composition between 1992 and 2006 in India. The present study adopts the World Health Organization (WHO) guidelines for appraising full immunization among children utilising three rounds of the National Family Health Survey. Twelve combinations of sex composition of surviving older siblings were constructed. Bivariate differentials and pooled multilevel logistic regression analysis were conducted to assess the trends and patterns of child immunization with respect to various categories of older surviving sibling composition. Although child immunization increased between 1992 and 2006, majority of all eligible children did not receive the recommended immunization. Further, full immunization significantly varies by twelve categories of siblings composition during 1992e2006. The probability of full immunization among male children who did not have any older surviving sibling was 60% in 2005e06, while it was just 26% among female children who had 1þ older surviving sister and brother. This study emphasizes the need to integrate sibling issues in child immunization as a prioritized component in the ongoing Universal Immunization Programme, which could be an effective step towards ensuring full immunization coverage among Indian children. Ó 2014 Elsevier Ltd. All rights reserved.
Keywords: Child immunization Gender Sibling composition India
1. Introduction The effectiveness of child immunization towards disease prevention, disability and death has been proven (Global Alliance for Vaccines and Immunization, 2012) and established as a costeffective intervention worldwide (Mulholland et al., 2012). In India, full immunization coverage has increased substantially at the national and sub-national levels over the last few years (Singh, 2013) from 35% in 1992 to 54% in 2008 (International Institute for Population Sciences, 2010). However, there is considerable divergence in administering the recommended immunization among socioeconomic groups, though immunization services are available at no cost in public health facilities (Singh, 2013; Madhavi, 2005). To illustrate, a national level survey shows that about two in five children belonged to illiterate mother received full immunization, * Corresponding author. Population, Health & Nutrition Research Programme (PHN-RP), Institute for Human Development, NIDM Building, IIPA Campus, IP Estate, Mahatama Gandhi Marg, New Delhi 110 002, India. E-mail addresses: [email protected] (P.K. Singh), sulabhap@rediffmail. com (S. Parasuraman). http://dx.doi.org/10.1016/j.socscimed.2014.02.017 0277-9536/Ó 2014 Elsevier Ltd. All rights reserved.
whereas the proportion was 75% among those children belonged to mother who had completed 10 and above years of schooling (International Institute for Population Sciences, 2010). Further, about three in five children in urban areas received immunization compared to two in five in rural areas. There is considerable regional disparity in child immunization e while some states from the southern region have coverage of over 70%, it is less than 40% among few central Indian states (International Institute for Population Sciences, 2010). Studies in low-and-middle income countries like India have documented the importance of mothers, households and community level factors associated with child immunization (Sheikh et al., 2011; Banerjee et al., 2010; Uddin et al., 2010). Additionally, factors such as accessibility to healthcare facility (Cockcroft et al., 2009), healthcare expenditure (Lauridsen and Pradhan, 2011), and infrastructure (Ghei et al., 2010) also affect levels of child immunization. In public health literature, gender differences in the provision of child immunization in the South Asia have been widely discussed (Singh, 2013; Chan and Yeoh, 2002; Arnold, 2001; Timaeus et al., 1998; Hill and Upchurch, 1995; Nag, 1991). Socioeconomic
146
P.K. Singh, S. Parasuraman / Social Science & Medicine 107 (2014) 145e153
difference in child immunization is common for majority of lowand-middle income countries (Hill and Upchurch, 1995; Edejer et al., 2005) however, gender gap is especially apparent in South Asia (Holmes, 2006; Das Gupta et al., 2003; Arnold, 2001). For instance, a recent review conducted by the WHO highlighted that gender differences in immunization coverage, favouring the male still exists in many South and South-East Asian countries (Hilber et al., 2010). There is evidence of lower full immunization coverage among female children than male children in India (Singh, 2013). A recent review based on over sixty studies conducted in different parts of India documented that childhood immunization coverage performance was better among male than among female children (Mathew, 2012). A survey carried out in Surat, India to calculate the incidence of measles among children under five years observed higher immunization coverage among male than to female children (Desai et al., 2002). Similarly, a study undertaken in Assam, India observed higher full immunization rate among male (65%) compared to female children (59%) based on the examination of vaccination cards and maternal recall (Phukan et al., 2009). An econometric analysis of vaccination data obtained from a sample of over 4333 rural children showed that 55% of the male children were fully vaccinated compared to 50% among female children (Borooah, 2004). Efforts to identify the underlying factors associated with malefemale difference in immunization highlighted that the persistence of gender discrimination resulted from the perceived greater economic, social, and religious utility of sons over daughters (Bhat and Zavier, 2003; Das Gupta et al., 2003). The cultural reasons for discrimination against daughters in the Indian context include the long history of the systematically marginalized status of women in terms of lower autonomy, restrictions on movement within the community and illiteracy, thus making daughters less socially valuable to parents than sons (Ghosh, 2012; Chamarbagwala, 2011; Das Gupta et al., 2003; Muhuri and Preston, 1991). In 1987, the ground breaking study done by Das Gupta in the state of Punjab, India emphasized that discriminatory practices against female children were not generalized, but highly selective. The study observed that such practices were highly concentrated among families with several girls (Das Gupta, 1987). The importance of death clustering, survival status of previous child, number of siblings and sex composition of older siblings on child healthcare including immunization has been documented in low-and-middle income countries including India (Arulampalam and Bhalotra, 2006; Das Gupta, 1990), Ghana (Garg and Morduch, 1998), and Bangladesh (Zenger, 1993). For instance, a study conducted in Matlab, Bangladesh found that girls with one or more older sisters were five times more at risk of dying than girls without older sisters. Similarly, for males, the mortality risk was higher for those with two or more older brothers, but the difference in mortality risk between the two was small. The authors also found that female children with two or more older brothers and male children with one or more older sister had very low levels of mortality (Muhuri and Preston, 1991). The review of available literature however, shows limited evidence of gender difference in full immunization by older sibling composition in the Indian context. Most of the studies were conducted during the early 1990s, period typically characterized as high fertility, low socioeconomic status, low status of women, poor healthcare knowledge and with limited policy initiatives. During the last one and half decades, India experienced considerable socioeconomic development along with major health policy initiatives including the Reproductive and Child Health Programme e 1997, National Population Policy e 2000, National Health Policy e 2002 etc. In all the policy initiatives, child immunization has been a
top priority (Madhavi, 2005). Since 1990s, the coverage of full immunization has increased both at national and across different socioeconomic groups (International Institute for Population Sciences and ORC Macro, 2007); the key question is whether full immunization is accessible to every child, irrespective of the sex composition? One could expect that the sibling difference has to be the lowest for healthcare that is freely available, like immunization. This study attempts to assess the progression of immunization for children aged 12e36 months over time with emphasis on gender difference by older surviving sibling composition. This study hypothesized that the gender difference in full immunization had declined over time among children with the same sex surviving sibling/s composition (female with older surviving sisters, and male with older surviving brothers), as compared to children with opposite sex surviving sibling/s composition (female with older surviving brothers, and male with older surviving sisters). Further, we also expected a declining gender gap in full immunization over time between male and female children with mixed older surviving siblings (one or more elder surviving brothers and sisters). 2. Data and methods 2.1. Data and sampling technique The present study uses data from three rounds of the National Family Health Survey (NFHS), similar to the Demographic and Health Survey (DHS) conducted during 1992e93, 1998e99 and 2005e06 (International Institute for Population Sciences and ORC Macro, 1995, 2000, 2007). All three rounds of the survey are nationally representative. The NFHS-1 covered a sample of 89,777 ever-married women aged 13e49, NFHS-2 covered 90,303 evermarried women aged 15e49, and NFHS-3 covered 124,385 women aged 15e49. A similar sampling scheme was adopted in all the three rounds of NFHS. The survey adopted a two-stage sample design in rural areas and a three-stage sample design in urban areas. In rural areas, the villages were selected at the first stage by using the Probability Proportional to Size (PPS) sampling scheme. The required number of households was selected at the second stage using systematic sampling. In urban areas, blocks were selected at the first stage, census enumeration blocks (CEB) containing approximately 150e200 households were selected at the second stage, and the required number of households were selected at the third stage using systematic sampling technique. The details of the sampling weights as well as the extensive information on survey design, data collection, and management procedures are described in the NFHS reports of the respective rounds (International Institute for Population Sciences and ORC Macro, 1995, 2000, 2007). 2.2. Defining outcome variable and sample size The outcome variable of the study is full immunization among children in the age group 12e36 months. According to the guidelines developed by the WHO, children are considered fully immunized when they receive a vaccination against tuberculosis (BCG); three doses of diphtheria, whooping cough (pertussis), and tetanus (DPT) vaccines; three doses of poliomyelitis (polio) vaccine and one dose of the measles vaccine by the age of twelve months. BCG should be given at birth or at first clinical contact, DPT and polio require three vaccinations at approximately 4, 8, and 12 weeks of age, and the measles vaccine should be given at age 12 months or soon after reaching 9 months of age. The present analysis is restricted to the last live birth (single and multiple) to women to make the estimates comparable and robust, as the information on child immunization in NFHS-1 (three live births in last four years)
P.K. Singh, S. Parasuraman / Social Science & Medicine 107 (2014) 145e153
NFHS-2 (two live births in last three years), and NFHS-3 (five live births in last five years) was not collected uniformly for all children under five years of age. The analytical sample size of the present study is restricted to 18,429, 15,795 and 15,993 children aged 12e 36 months respectively in NFHS-1, NFHS-2, and NFHS-3. The missing cases were negligible and therefore, excluded from the analysis. Information on child immunization was collected from the immunization cards shown by household members during the survey or in the absence of the immunization card, information was gathered from the mother of the respective child. In NFHS-1, about 61% mothers shown child immunization cards, and it increased to 69% in NFHS-2 and 76% in NFHS-3. The upper age limit was chosen as 36 months to maximize the use of available data. Further, the advantage of considering the immunization status of the last child is to minimize recall errors. Previous studies have shown that the precision with which mothers recall child healthcare including immunization deteriorates following the last birth (Luman et al., 2009). Besides, considering the last birth could reduce the mother’s level of unobserved heterogeneity (Arulampalam and Bhalotra, 2006). The present study takes into consideration the gender pattern of older surviving siblings with reference to the last birth. 2.3. Defining older surviving sibling composition and other predictor variables All the three rounds of NFHS asked every eligible woman in the age group 15e49 years, her complete birth history including the sex, order of birth and survival status. Using this information, several categories were created to represent the composition of older siblings based on the number and sex of older siblings’, while also taking into account the sex of the last born child. The index of the sex-sibling composition is classified into twelve categories e six older surviving sibling categories for each male and female child.
147
The six sibling categories are: ‘none’ (no older surviving brother and no older surviving sister); ‘one surviving older brother and no surviving older sister’; ‘one surviving older sister and no surviving older brother’; ‘two or more surviving older brothers and no older sister’; ‘two or more surviving older sisters and no older brother’; and a ‘mixed’ (1þ older surviving brothers and 1þ sisters) category of surviving older brothers and sisters. To examine the net effect of older surviving sibling composition on immunization during 1992e 2006, selected socioeconomic and demographic predictors have been included in the analysis. These indicators are based on their theoretical and observed importance applied in literature and availability of information in all three rounds of survey for better comparability. A detailed description of selected variables is provided in Table 1. 2.4. Analytical approach First, bivariate analyses were carried out to understand the proportion of the difference in full immunization by twelve categories of older surviving sibling composition and other background variables. To test the significance of association in full immunization by selected background characteristics, Chi-squared tests were performed. As the sampling design of the NFHS offers an opportunity to make all the three rounds of data comparable (Mishra et al., 2004), earlier studies have pooled the different rounds of DHS/NFHS datasets to observe changes over time (Singh, 2013). In order to examine the trend of full immunization coverage over time, the study fit a pooled multilevel logistic regression model while adjusting for important socioeconomic, demographic and contextual variables. The interaction results between time and sibling compositions are presented as a set of predicted probabilities with 95% confidence intervals (CI) of being fully immunized for better representation. The Wald test was used to test the significance of the interaction between sibling composition and survey
Table 1 Description of exposure variables used in modelling full immunization among children aged 12e36 months in India, NFHS 1992e2006. Background variables Individual level variables Older surviving sibling composition Current age of the child Status of the last child Preceding birth interval Mother’s childcare burden Mother’s age at last birth Mother’s education Mother’s occupation Mother’s mass media exposure Household level variables Religion Social groups Household size Household wealth quintile Contextual level variables Type of residence Region of residence
Description Constructed for the most recent surviving child between 12 and 36 months, based on mother’s complete birth history, that takes into account the sex of the most recent child, the sex composition as well as number of the surviving siblings and birth order. Based on mother’s reporting of year of birth of the last child, grouped as follows: 12e23, and >23 months Based on the mother’s reporting of the last children as wanted then, wanted later, wanted no more. The status of the child is then categorized as: wanted (wanted then) and unwanted (wanted later þ wanted no more) Indicates mother’s preceding birth interval with reference to the last child, grouped as: 24 months and >24 months Indicates women’s total number of births in the 3-year period preceding the birth of the index child: No burden and At least one burden Based on women’s reporting of year of birth of the last child and current age of women and grouped as follows: <20, 20e29, and >29 Defined using years of schooling and they were grouped as: Illiterate, 1e4 years, 5e7 years, 8e9 years, 10 and above years Identification of women’s occupation based on self-reporting and grouped as follows: not working, agricultural/domestic/ labour, and others Assessed by considering how often women read the newspaper, listen to the radio and watch television or cinema categories as: no exposure and any exposure Based on women’s self reporting religious groups as: Hindu, Muslim, and Others Identification of the social group was based on the women’s self-reporting as: Others, Scheduled Tribes, and Scheduled Castes Based on number of members in the household grouped as: up to 5, 6e9 and >9 Index based on household amenities, assets and durables derived by factor analysis used for the computation of the wealth index. Households were categorized into quintiles as follows: Richest, Richer, Middle, Poorer, and Poorest Children’s current place of residence: Urban, and Rural NFHS demarcations of regions based on geographical locations and cultural settings categorized as: North (Delhi, Haryana, Himachal Pradesh, Jammu and Kashmir, Punjab, Rajasthan and Uttarakhand); Central (Chhattisgarh, Madhya Pradesh and Uttar Pradesh); East (Bihar, Jharkhand, Orissa and West Bengal); West (Goa, Gujarat and Maharashtra); South (Andhra Pradesh, Karnataka, Kerala and Tamil Nadu); Northeast (Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim and Tripura)
148
P.K. Singh, S. Parasuraman / Social Science & Medicine 107 (2014) 145e153
year. Owing to the binary nature of the dependent variable (full immunization: yes ¼ 1, otherwise ¼ 0), the multilevel model with logit link function can be described as follows:
"
pips ln 1 pips
# ¼ a þ xips b þ wps g þ zs h þ ups þ vs
where ln(pips/(1 pips)) is the logit in which pips is the probability of children ‘i’ in Primary Sampling Unit (PSU) ‘p’ in state ‘s’ receiving full immunization; xips, wps, and zs are vectors of individual/household level, PSU level, and state level characteristics; a is a constant, while b, g, and h are vectors of estimated parameter coefficients; and ups and vs are unexplained residual terms at the PSU and state level, respectively. The study used penalized quasi-likelihood (PQL) approximate estimation procedure, which has been found to be the least biased (Rasbash et al., 2009) in the case of binary response. Since the study considered a range of covariates in the models, we examined for multicollinearity with variance inflation factors, all of which were much lower than 2.5, suggesting that the possibility of high multicollinearity was ostensible. The analysis has been performed using Stata version 10 (Statacorp, 2007). 3. Results 3.1. Description of the study population Table 2 shows the percentage of last born children in each descriptive category in last three years preceding the survey. During 1992e2006, percentage of male children was higher as compared with female counterparts. Results show higher percentage of children belonged to either male or female with 1þ older surviving brother and sister or to those who did not have any older surviving siblings. Nearly three in five children belonged to the age group 12e23 months. The unwanted status of last child increased from 20% in 1992e93 to 28% in 2005e06. The mother’s childcare burden marginally declined from 55% in 1992e93 to 53% in 2005e06. Majority of the mothers were illiterate and unemployed in all three rounds of surveys. Exposure to any type of mass media improved from 46% in 1992e93 to 69% in 2005e06. The sample distribution during 1992e2006 indicates that majority of the children were Hindus and from the ‘others’ social group. The distribution indicated more children in poor households than in higher socioeconomic households.
whose mother was exposed to any means of mass media received higher full immunization. During 1992e2006, the gap in immunization between the rich and the poor was almost three-fold. Rural children and those residing in central regions received lower full immunization during 1992e2006, whereas children belonged to urban areas and from the south region utilized higher rates of full immunization. 3.3. Sibling composition and full immunization during 1992e2006: a pooled multilevel analysis A multilevel regression model has been applied after pooling three rounds of survey to examine the net effect of sibling composition on full immunization (Appendix 1). The results suggest that factors such as sibling composition, age of the child, mother’s childcare burden, mother’s age, education, mass media exposure, religion, household size, wealth quintile, and region of residence significantly associated with the full immunization. As the prime aim of this study is to examine the trend in full immunization for the last born child and differentials according to child’s gender and older surviving sibling composition, adjusted predicted probabilities has been estimated from the pooled multilevel model (Table 4). The two-way interaction between the twelve categories of sibling composition and three categories of survey period were statistically significant after adjusting for other background variables in the model. The result clearly suggests that full immunization across the twelve categories of sibling compositions have changed significantly over time. In order to present the results more comprehensively, the difference between male compositions with a similar category of female compositions has been demonstrated. To illustrate, we have compared the similar sibling composition category between male and female children to understand the differences in full immunization. The findings confirm that with one exception (males who had only one older surviving brother e females who had only one older surviving brother), gender difference in full immunization was apparent across all sibling compositions during 1992e2006. Moreover, the results show a growing gender difference in full immunization coverage in a few categories of sibling composition during 1992e2006. For instance, the gap in full immunization between male and female who had 2þ older surviving sisters were 8% in 1992e93, that increased to about 14% in 2005e06. Similarly, those male and female who had one older surviving sisters, the gap in full immunization had increased from 2% in 1992e93 to 5% in 2005e06.
3.2. Differentials in full immunization coverage during 1992e2006 4. Discussion Differentials in full immunization by selected individuals, households and contextual level characteristics during 1992e2006 are presented in Table 3. The trend suggests that full immunization coverage at the national level increased from 36% in 1992e93 to 45% during 2005e06. Considerable difference in full immunization was evident by older sibling composition. For instance, in all three rounds of survey the lowest full immunization was observed among female children with 1þ older surviving brother and 1þ sister. However, male children who did not have any older surviving sibling received highest percentage of full immunization. The full immunization was lower among those children who had at least one older surviving sibling below the age of five years. Children born to women aged above 30 years received the lowest percentage of full immunization during 1992e2006. Differences in full immunization coverage by mother’s education were large. For example, in 2005e06, about 72% of children born to mothers who had completed ten or more years of schooling received full immunization, whereas the corresponding figure was less than 28% among children born to illiterate mothers. Children
The overall trend suggests a significant difference in full immunization among last born children according to the number and gender of older sibling compositions during 1992e2006. The analysis confirms that immunization coverage for female children worsened with the number of surviving older sisters, similarly immunization coverage for male children declined with the increase in number of older surviving brothers. On the other hand, during 1992e2006, a higher coverage of full immunization was observed among those male and female children who either did not have any older surviving sibling or had one older opposite sex sibling. Previous studies also found that both female and male children born after multiple same-sex siblings had lower immunization, whereas male children with multiple older sisters had the highest rate of immunization (Pande, 2003). Literature suggests that despite the presence of strong son preference in countries like India, parents may selectively favour a certain sex-birth-order to attain their desired sex composition (Pande, 2003). Indeed, in India the percentage of ever married
P.K. Singh, S. Parasuraman / Social Science & Medicine 107 (2014) 145e153
149
Table 2 Percentage distribution of children aged 12e36 months according to selected background characteristics, India, NFHS 1992e2006. Background variables
1992e93 %
1998e99 n
%
2005e06 n
%
n
Sex of the child Male Female
51.2 48.8
9591 8910
52.5 47.5
8424 7371
54.4 45.6
8619 7374
Older surviving sibling composition Male with no older survival sibling Female with no older survival sibling Male with only 1 brother and no sister Male with only 1 sister and no brother Female with only 1 brother and no sister Female with only 1 sister and no brother Male with 2þ brothers and no sister Male with 2þ sisters and no brother Male with 1þ brothers and 1þ sisters Female with 2þ brothers and no sister Female with 2þ sisters and no brother Female with 1þ brothers and 1þ sister
12.9 12.4 6.2 6.2 6.3 5.8 3.6 4.2 18.1 3.5 3.6 17.2
2418 2311 1195 1155 1204 1060 650 775 3326 632 664 3039
13.9 12.6 7.2 7.0 7.0 5.8 2.9 4.5 17.0 3.3 3.2 15.5
2232 1991 1165 1132 1063 905 465 718 2712 484 511 2417
14.9 12.7 7.4 8.2 7.1 5.9 3.0 4.6 16.2 2.5 3.6 13.6
2506 2240 1240 1362 1180 1017 442 738 2331 404 531 2002
Child current age 12e23 months >23 months
60.3 39.7
10,972 7457
57.4 42.6
8988 6807
56.5 43.5
8978 7015
Status of the last child Wanted Unwanted
80.5 19.5
14,799 3618
76.8 23.2
12,087 3704
72.0 28.0
11,992 3996
Preceding birth interval 24 months >24 months
26.2 73.8
3643 10,035
26.4 73.6
3093 8461
28.7 71.3
3255 7958
Mother’s childcare burden No surviving children At least one
45.4 54.6
8354 10,075
45.5 54.5
7236 8559
47.2 52.8
7925 8068
Mother’s age at last birth <20 20e29 >29
21.3 61.4 17.2
3515 11,683 3231
21.6 64.5 13.9
2985 10,304 2506
18.5 66.4 15.2
2474 10,753 2766
Mother’s education Illiterate 1e4 years 5e7 years 8e9 years 10 and above years
63.8 6.6 11.6 7.0 11.0
10,757 1287 2332 1536 2517
53.3 8.5 14.0 9.2 15.1
7896 1347 2207 1653 2692
48.3 6.6 14.9 12.5 17.7
6181 1140 2393 2382 3897
Mother’s occupation Not working Agricultural/domestic/labour Others
70.7 19.1 10.2
12,857 3571 2001
65.7 27.6 6.6
10,575 4059 1161
63.0 32.7 4.3
10,365 4544 1084
Mother’s mass media exposure No exposure Any exposure
54.1 45.9
9083 9346
45.7 54.3
6620 9175
31.2 68.8
3735 12,258
Religion Hindu Muslim Others
81.4 10.6 8.0
14,051 2419 1956
79.3 15.2 5.5
11,718 2249 1808
78.1 17.2 4.6
11,071 2655 2250
Social groups Others Scheduled Castes Scheduled Tribes
83.9 9.9 6.2
13,875 2233 2318
70.1 20.1 9.6
10,526 2883 2289
69.8 20.2 9.4
10,114 2744 2495
Household size Up to 5 members 6e9 >9 members
31.5 44.5 24.2
6121 8111 4197
35.4 43.4 21.2
5681 6924 3190
40.5 43.1 16.4
7018 6642 2333
Household wealth quintile Poorest Poorer Middle Richer Richest
23.9 23.7 20.2 16.1 16.1
4194 4031 3834 3461 2909
26.6 25.3 19.5 15.1 13.6
4297 4111 3417 2360 1610
24.8 22.0 19.2 17.9 16.0
2722 2851 3220 3545 3655
(continued on next page)
150
P.K. Singh, S. Parasuraman / Social Science & Medicine 107 (2014) 145e153
Table 2 (continued ) Background variables
1992e93
1998e99
2005e06
%
n
%
n
%
Place of residence Urban Rural
23.1 76.9
5095 13,334
23.0 77.0
4275 11,520
26.6 73.4
6272 9721
Region of residence North Central East Northeast West South Total
11.7 29.1 22.5 4.3 13.1 19.3 100
4124 4278 3070 2039 1982 2936 18,429
13.0 24.4 24.3 3.7 13.8 20.8 100
3741 2909 2950 2206 1670 2319 15,795
11.8 29.3 25.5 3.9 13.1 16.4 100
2447 3791 2532 3032 1855 2336 15,993
women in the age group 15e49, who want at least one daughter is almost as equal as (81%) the percentage who want at least one son (International Institute for Population Sciences and ORC Macro, 2007). This suggests that in societies with a strong gender bias, the preferred sex composition often includes a daughter and the possibility of bias in immunization for a male with two or more elder brothers could be higher than a male who did not have any siblings or had all opposite sex siblings. Evidence suggests greater sibling rivalry in resource distribution including parental time allocation to children’s healthcare when the number of sons is more in the family than daughters (Garg and Morduch, 1998). In this case, quite often, the younger son has to bear the adverse consequences in terms of lower education, cognitive skills and healthcare, since the household resource allocation has already been shifted to the elder brother. For example, if the rate of return on investment in healthcare is greater for the elder male than for the younger, the elder brother will receive more of such investments (Behrman et al., 1982). The present study shows an increasing gender gap in immunization by cross-sibling comparison. For instance, over time, there has been a two-fold increase in the difference in full immunization between male and female children with a mixed older surviving sibling composition (1þ older surviving brother and 1þ sister). This continuous gender difference in immunization could be linked with India’s well documented history of son preference (Das Gupta et al., 2003; Dyson and Moore, 1983). For instance, according to the third round of NFHS, over one in four married women in the age group 15e49, expressed their desire for more sons than daughters, whereas the percentage who wanted more daughters than sons was less than three percent (International Institute for Population Sciences and ORC Macro, 2007). The increasing gender difference in full immunization supports the evidence that the existence of rigid patrilineal kinship systems, whereby only sons are allowed to inherit family assets and wealth, appear to be primarily responsible for continuing gender difference, even in the face of economic development and the rising status of women (Das Gupta et al., 2003; Das Gupta and Shuzhuo, 1999; Dyson and Moore, 1983). The preference of sons over daughters is the product of prolonged societal, cultural and religious practices that promotes son(s) as a symbol of power and prestige in the community (Kishor, 1993; Pande, 2003; Choi and Lee, 2006). In these circumstances, the overall allocation of available community and household level resources could be significantly shifted towards the preferred sex.
4.1. Potential limitations This study has a few limitations. Child immunization data have been collected from two sources: vaccination cards and mothers’ reporting. Using data from both mothers’ reports and
n
immunization cards is more inclusive than data from cards alone. Previous studies have evaluated the quality of information from mothers’ reports. Some of them have underscored the high validity of mother’s recall, while other studies point to significant recall errors resulting in either overestimation or underestimation (Luman et al., 2009). In spite of potential sources of errors, the DHS (or NFHS) is considered one of the best sources of population-based information on health and healthcare service utilization in low-and middle-income countries (Murray et al., 2003). Thus, this study considers immunization coverage based on the NFHS data to be of adequate quality and validity against which other measurements of the same variables can be compared. There are other potential factors such as distance, quality of immunization services, behaviour and attitude of health personnel that could determine the full immunization coverage and act separately for male and female children, which have not been included in this study due to data constraints. This study cannot examine the causality as the study design and available data have certain restrictions.
4.2. Conclusion and policy implications According to recent estimates, about 22.6 million children were not fully vaccinated and remained at risk for diphtheria, tetanus, and pertussis and other vaccine-preventable causes of morbidity and mortality worldwide, and about 30% (6.8 million) lived in India alone (Centre for Disease Control and Prevention, 2013). The findings of the present study have potential implications for India’s health policy that has been insufficient in dealing with the sibling difference in immunization over time. It is necessary to recognize at the policy level that besides financial costs, other factors could also restrict immunization coverage. As evidences suggests that balanced gender composition of offspring may be important to parents in India, where female born after multiple same sex sibling face lower priority in healthcare (Chamarbagwala, 2011). More indepth researches are needed to examine the underlying factors that affect immunization coverage among children by sex compositions. In addition, it is important to raise awareness about the importance of child vaccination, and the role of local health workers is vital in reaching households with higher order births, and especially children with two or more elder same sex siblings. Adequate attention has not been extended to assess the full immunization coverage considering sibling compositions; rather gender (male-female) difference per se has only been considered. Thus, there is need to adopt inclusive approach to enhance the coverage of full immunization irrespective of sibling compositions. For instance, providing financial incentives could be an effective strategy to minimize full immunization differences by sibling compositions. Further, this study emphasizes the need to integrate sibling issues in child immunization as a prioritized component in
P.K. Singh, S. Parasuraman / Social Science & Medicine 107 (2014) 145e153
151
Table 3 Percentage of children of ages 12e36 months who received full immunization by selected background characteristicsa, India, NFHS 1992e2006. Background characteristic
1991e92
1998e99
2005e06
Pooled 1992e2006
Sex of the child Male Female
[p < 0.001] 37.1 34.9
[p < 0.001] 43.1 39.5
[p < 0.001] 46.0 43.1
[p < 0.001] 42.0 38.9
Older surviving sibling composition Male with no older survival sibling Female with no older survival sibling Male with only 1 brother and no sister Male with only 1 sister and no brother Female with only 1 brother and no sister Female with only 1 sister and no brother Male with 2þ brothers and no sister Male with 2þ sisters and no brother Male with 1þ brothers and 1þ sisters Female with 2þ brothers and no sister Female with 2þ sisters and no brother Female with 1þ brothers and 1þ sister
[p < 0.001] 45.6 44.4 42.2 44.7 41.3 40.7 30.3 38.2 27.9 31.4 34.6 24.7
[p < 0.001] 53.2 49.3 48.5 51.1 49.1 46.9 30.5 49.7 29.4 33.0 35.7 26.4
[p < 0.001] 56.7 54.7 50.7 54.1 51.1 53.1 40.3 49.1 29.9 35.3 36.7 27.0
[p < 0.001] 51.9 49.4 47.2 50.3 47.2 46.8 33.5 45.5 29.0 32.9 35.7 25.9
Child current age 12e23 months >23 months
[p < 0.001] 35.0 37.7
[p ¼ 0.042] 40.8 42.2
[p < 0.001] 43.5 46.2
[p < 0.001] 39.5 42.0
Status of the last child Wanted Unwanted
[p ¼ 0.031] 36.4 34.7
[p < 0.001] 42.8 36.7
[p < 0.001] 48.4 34.9
[p < 0.001] 42.1 35.4
Preceding birth interval 24 months >24 months
[p < 0.001] 35.8 32.0
[p ¼ 0.008] 39.6 37.0
[p ¼ 0.118] 40.9 38.9
[p ¼ 0.002] 38.0 36.4
Mother’s childcare burden No surviving children At least one
[p < 0.001] 40.0 32.8
[p < 0.001] 46.0 37.5
[p < 0.001] 51.4 38.6
[p < 0.001] 45.7 36.1
Mother’s age at last birth <20 20e29 >29
[p < 0.001] 35.2 38.8 27.3
[p < 0.001] 37.3 45.0 30.7
[p < 0.001] 43.1 47.0 36.4
[p < 0.001] 38.2 43.5 31.2
Mother’s education Illiterate 1e4 years 5e7 years 8e9 years 10 and above years
[p < 0.001] 24.0 44.4 49.6 62.3 70.3
[p < 0.001] 26.4 46.7 53.9 59.0 68.6
[p < 0.001] 27.5 47.8 52.5 60.8 72.0
[p < 0.001] 25.7 46.3 52.0 60.7 70.5
Mother’s occupation Not working Agricultural/domestic/labour Others
[p < 0.001] 36.6 33.0 37.8
[p < 0.001] 42.4 36.6 50.7
[p < 0.001] 48.6 35.4 56.8
[p < 0.001] 42.1 35.2 45.2
Mother’s mass media exposure No exposure Any exposure
[p < 0.001] 23.4 51.0
[p < 0.001] 25.3 54.8
[p < 0.001] 26.7 52.8
[p < 0.001] 24.8 52.8
Religion Hindu Muslim Others
[p < 0.001] 36.7 25.6 56.4
[p < 0.001] 41.7 31.5 65.9
[p < 0.001] 45.6 37.2 63.1
[p < 0.001] 41.5 31.2 62.4
Social groups Others Scheduled Castes Scheduled Tribes
[p < 0.001] 38.8 28.1 24.1
[p < 0.001] 44.1 39.5 25.6
[p < 0.001] 49.3 41.1 33.5
[p < 0.001] 44.6 36.1 27.9
Household size Up to 5 members 6e9 >9 members
[p < 0.001] 40.2 33.8 34.8
[p < 0.001] 47.7 38.1 37.4
[p < 0.001] 49.6 40.3 43.7
[p < 0.001] 46.0 37.3 38.0
Household wealth quintile Poorest Poorer Middle Richer Richest
[p ¼ 0.020] 17.3 22.2 35.5 49.4 65.0
[p ¼ 0.010] 21.1 29.7 42.8 53.5 63.8
[p < 0.001] 24.6 34.7 48.7 56.6 71.0
[p < 0.001] 21.0 28.9 42.3 53.2 66.6
Place of residence Urban
[p < 0.001] 52.2
[p < 0.001] 57.6
[p < 0.001] 58.5
[p < 0.001] 56.1 (continued on next page)
152
P.K. Singh, S. Parasuraman / Social Science & Medicine 107 (2014) 145e153
Table 3 (continued ) Background characteristic
1991e92
1998e99
2005e06
Pooled 1992e2006
Rural
31.2
36.5
39.6
35.6
Region of residence North Central East Northeast West South Total
[p < 0.001] 42.5 23.0 21.6 20.7 60.8 55.3 36.1
[p < 0.001] 41.6 21.8 27.8 22.8 65.7 67.0 41.4
[p < 0.001] 45.8 31.0 45.9 35.7 54.8 60.3 44.6
[p < 0.001] 43.3 25.5 32.1 26.2 60.3 60.7 40.5
a
Figures in parentheses are the p < value obtained from c2 test applied for each variable.
Table 4 Predicted probabilitya,b (95% Confidence Interval) obtained from the pooled multilevel regression analysis of child immunization (aged 12e36 months) for interaction between older surviving sibling compositions and survey period, India, NFHS 1992e2006. Interaction effect between older surviving sibling composition and time
Male Male Male Male Male Male Male
compositions with no older survival sibling with only 1 brother and no sister with only 1 sister and no brother with 2þ brothers and no sister with 2þ sisters and no brother with 1þ brothers and 1þ sisters
Female compositions Female with no older survival sibling Female with only 1 brother and no sister Female with only 1 sister and no brother Female with 2þ brothers and no sister Female with 2þ sisters and no brother Female with 1þ brothers and 1þ sister Differencesc Male with no older survival sibling e Female with no older survival sibling Male with only 1 brother and no sister e Female with only 1 brother and no sister Male with only 1 sister and no brother e Female with only 1 sister and no brother Male with 2þ brothers and no sister e Female with 2þ brothers and no sister Male with 2þ sisters and no brother e Female with 2þ sisters and no brother Male with 1þ brothers and 1þ sisters e Female with 1þ brothers and 1þ sister
1992e93 Predicted probability
1998e99 95% CI
Predicted probability
2005e06 95% CI
Predicted probability
95% CI
0.47 0.42 0.45 0.30 0.41 0.26
[0.46e0.49] [0.40e0.45] [0.42e0.47] [0.27e0.33] [0.39e0.44] [0.24e0.27]
0.53 0.48 0.51 0.34 0.46 0.27
[0.51e0.55] [0.45e0.50] [0.49e0.54] [0.30e0.37] [0.43e0.50] [0.26e0.30]
0.61 0.54 0.58 0.37 0.50 0.30
[0.59e0.63] [0.51e0.56] [0.55e0.60] [0.34e0.41] [0.47e0.53] [0.29e0.32]
0.44 0.43
[0.42e0.46] [0.40e0.45]
0.50 0.47
[0.48e0.52] [0.45e0.50]
0.57 0.54
[0.56e0.59] [0.51e0.56]
0.43
[0.40e0.45]
0.45
[0.43e0.48]
0.53
[0.50e0.56]
0.30 0.34 0.23
[0.27e0.33] [0.31e0.37] [0.22e0.24]
0.31 0.33 0.24
[0.28e0.35] [0.30e0.36] [0.23e0.26]
0.36 0.36 0.26
[0.33e0.40] [0.33e0.40] [0.25e0.28]
3.23
2.59
3.20
0.28
0.42
0.34
2.11
5.77
4.57
0.48
2.11
1.26
7.65
12.99
13.73
2.77
3.31
4.20
All the predicted probabilities were significantly different at p < 0.001 (c2 ¼ 243.45) in Wald test. Predicted probability adjusted for child age, mother’s childcare burden, preceding birth interval, wanted status of child, mother’s age at last birth, mother’s education, mother’s occupation, mother’s mass media exposure, religion, social groups, household size, household wealth index, place of residence, and region of residence. c Difference calculated as: male compositions female compositions*100. a
b
the ongoing Universal Immunization Programme, which could be an effective step towards ensuring full immunization coverage among all Indian children. The study recommends further research to examine why there has been little progress in reducing the differentials in child immunization by sibling composition. In future, research is required at regional, sub-regional and across different socioeconomic strata to explore further dynamics related to sibling difference in immunization. Future research should also examine the cultural and economic perspectives on sibling differences by explicitly investigating parental attitudes toward social norms.
Acknowledgement The authors are grateful to the editor and four anonymous reviewers for their insightful feedbacks on the earlier draft of the manuscript. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.socscimed.2014.02.017.
P.K. Singh, S. Parasuraman / Social Science & Medicine 107 (2014) 145e153
References Arnold, F., 2001. Son preference in South Asia. In: Sathar, Z.A., Phillips, J.F. (Eds.), Fertility Transition in South Asia. Oxford University Press, Oxford, pp. 278e297. Arulampalam, W., Bhalotra, S., 2006. Sibling death clustering in India: state dependence versus unobserved heterogeneity. Journal of Applied Statistics 169, 829e848. Banerjee, A.V., Duflo, E., Glennerster, R., Kothari, D., 2010. Improving immunisation coverage in rural India: clustered randomised controlled evaluation of immunisation campaigns with and without incentives. BMJ 340, c2220. Behrman, J., Pollak, R., Taubman, P., 1982. Parental preferences and provision for progeny. Journal of Political Economy 90, 52e73. Bhat, P.N.M., Zavier, A.J.F., 2003. Fertility decline and gender bias in Northern India. Demography 40, 637e657. Borooah, V.K., 2004. Gender bias among children in India in their diet and immunisation against disease. Social Science & Medicine 58, 1719e1731. Centre for Disease Control and Prevention, 2013. Global routine vaccination coverage, 2012. Morbidity and Mortality Weekly Report 62, 858e861. Chamarbagwala, R., 2011. Sibling composition and selective gender-based survival bias. Journal of Population Economics 24, 935e955. Chan, A., Yeoh, B., 2002. Gender, family and fertility in Asia: an introduction. AsiaPacific Population Journal 17, 5e10. Choi, J.Y., Lee, S.H., 2006. Does prenatal care increase access to child immunization? Gender bias among children in India. Social Science & Medicine 63, 107e117. Cockcroft, A., Andersson, N., Omer, K., Ansari, N.M., Khan, A., Chaudhry, U.U., Ansari, U., 2009. One size does not fit all: local determinants of measles vaccination in four districts of Pakistan. BMC International Health and Human Rights 9 (Suppl. 1), S4. Das Gupta, M., 1987. Selective discrimination against female children in rural Punjab, India. Population and Development Review 13, 77e100. Das Gupta, M., 1990. Death clustering, mothers’ education and the determinants of child mortality in rural Punjab, India. Population Studies 44, 489e505. Das Gupta, M., Shuzhuo, L., 1999. Gender Bias in China, the Republic of Korea, and India 1920-90. World Bank Policy Research Working Paper no. 2140. Available at: http://elibrary.worldbank.org/content/workingpaper/10.1596/1813-94502140 (accessed 01.10.13.). Das Gupta, M., Zhenghua, J., Bohua, L., Zhenming, X., Chung, W., Hwa-Ok, B., 2003. Why is son preference so persistent in East and South Asia? A cross-country study of China, India and the Republic of Korea. Journal of Development Studies 40, 153e187. Desai, V.K., Kapadia, S.J., Kumar, P., Nirupam, S., 2002. Study of measles incidence and vaccination coverage in slums of Surat city. Indian Journal of Pediatrics 69, 1037e1040. Dyson, T., Moore, M., 1983. On kinship structure, female autonomy, and demographic behavior in India. Population and Development Review 9, 35e60. Edejer, T.T., Aikins, M., Black, R., Wolfson, L., Hutubessy, R., Evans, D.B., 2005. Cost effectiveness analysis of strategies for child health in developing countries. BMJ 331, 1177. Garg, A., Morduch, J., 1998. Sibling rivalry and the gender gap: evidence from child health outcomes in Ghana. Journal of Population Economics 11, 471e493. Ghei, K., Agarwal, S., Subramanyam, M.A., Subramanian, S.V., 2010. Association between child immunization and availability of health infrastructure in slums in India. Archives of Pediatrics & Adolescent Medicine 164, 243e249. Ghosh, R., 2012. Child mortality in India: a complex situation. World Journal of Paediatrics 8, 11e18. Global Alliance for Vaccines and Immunization, 2012. Global Immunization News. Available at: http://www.who.int/immunization/GIN_June_2012.pdf (accessed 12.06.12.). Hilber, A.M., Bosch-Capblanch, X., Schindler, C., Beck, L., Sécula, F., McKenzie, O., Gari, S., Stuckli, C., Merten, S., 2010. Gender and Immunization: Summary
153
Report for SAGE, 2010. Partner WHO e Initiative for Vaccine Research. World Health Organization, Geneva: Switzerland. Hill, K., Upchurch, D.M., 1995. Gender differences in child health: evidence from the demographic and health surveys. Population and Development Review 21, 127e151. Holmes, J., 2006. Do community factors have a differential impact on the health outcomes of boys and girls? Evidence from rural Pakistan. Health Policy and Planning 21, 231e241. International Institute for Population Sciences, ORC Macro, 2000. National Family Health Survey (NFHS e 2), 1998e99: India. IIPS, Mumbai. International Institute for Population Sciences, ORC Macro, 2007. National Family Health Survey (NFHS e 3), 2005e06: India, vol. I. IIPS, Mumbai. International Institute for Population Sciences, ORC Macro, 1995. National Family Health Survey (NFHS e 1), 1992e93: India. IIPS, Mumbai. International Institute for Population Sciences, 2010. District Level Household and Facility Survey (DLHS-3), 2007e08. IIPS, Mumbai. Kishor, S., 1993. May god give sons to all: gender and child mortality in India. American Sociological Review 58, 247e265. Lauridsen, J., Pradhan, J., 2011. Socio-economic inequality of immunization coverage in India. Health Economics Review 1, 11. Luman, E.T., Ryman, T.K., Sablan, M., 2009. Estimating vaccination coverage: validity of household-retained vaccination cards and parental recall. Vaccine 27, 2534e 2539. Madhavi, Y., 2005. Vaccine policy in India. PLoS Medicine 2, e127. Mathew, J.L., 2012. Inequity in childhood immunization in India: a systematic review. Indian Pediatrics 49, 203e223. Mishra, V., Roy, T., Retherford, R.D., 2004. Sex differentials in childhood feeding, health care, and nutritional status in India. Population and Development Review 30, 269e295. Muhuri, P.K., Preston, S.H., 1991. Effects of family composition on mortality differentials by sex among children in Matlab, Bangladesh. Population and Development Review 17, 415e434. Mulholland, E.K., Griffiths, U.K., Biellik, R., 2012. Measles in the 21st century. New England Journal of Medicine 366, 1755e1757. Murray, C.J., Shengelia, B., Gupta, N., Moussavi, S., Tandon, A., Thieren, M., 2003. Validity of reported vaccination coverage in 45 countries. The Lancet 362, 1022e1027. Nag, M., 1991. Sex preference in Bangladesh, India and Pakistan, and its effect on fertility. Demography India 20, 163e185. Pande, R., 2003. Selective gender differences in childhood nutrition and immunization in rural India: the Role of Siblings. Demography 40, 395e418. Phukan, R.K., Barman, M.P., Mahanta, J., 2009. Factors associated with immunization coverage of children in Assam, India: over the first year of life. Journal of Tropical Pediatrics 55, 249e252. Rasbash, J., Charlton, C., Browne, W.J., Healy, M., Cameron, B., 2009. MLwiN Version 2.1. Centre for Multilevel Modelling. University of Bristol, Bristol. Sheikh, S., Ali, A., Zaidi, A.K., Agha, A., Khowaja, A., Allana, S., Qureshi, S., Azam, I., 2011. Measles susceptibility in children in Karachi, Pakistan. Vaccine 29, 3419e 3423. Singh, P.K., 2013. Trends in child immunization across geographical regions in India: focus on urban-rural and gender differentials. PLoS ONE 8, e73102. Statacorp, 2007. Stata Statistical Software: Release 10. Statacorp LP, College Station, Texas: USA. Timaeus, I., Harris, K., Fairbairn, F., 1998. Can Use of Health Care Explain Sex Differentials in Child Mortality in the Developing World. Too Young to Die: Genes or Gender. Population Division, United Nations, New York. Uddin, M.J., Koehlmoos, T.P., Saha, N.C., Khan, I.A., Shamsuzzaman, 2010. Child immunization coverage in rural hard-to-reach areas of Bangladesh. Vaccine 28, 1221e1225. Zenger, E., 1993. Sibling neonatal mortality risks and birth spacing in Bangladesh. Demography 30, 477e488.